Financing Constraints and the Timing of Innovations in the German Services Sector

Using newly available data at the firm level, this study provides convincing evidence of the importance of financial constraints in explaining the timing of innovations in the German services sector. Based on a dynamic model of firms' optimal R&D behavior under financial constraints, we estimate various versions of an econometric specification of the model with dichotomous innovation data by using a univariate ordered probit model and a newly developed modification of it. The modified econometric estimation strategies takes into account that some of the regressors are measured on an ordinal scale. Our results are consistent with the theoretical view that, because of capital markets imperfections, internal finance should be an important determinant of innovative activities by private firms in the manufacturing sector as well as in the services sector.

Indirect estimation of linear models with ordinal regressors. A Monte Carlo study and some empirical illustrations

This paper investigates the effects of ordinal regressors in linear regression models. Each ordered categorical variable is interpreted as a rough measurement of an underlying continuous variable as it is often done in microeconometrics for the dependent variable. It is shown that using ordinal indicators only leads to correct answers in a few special cases. In most situations, the usual estimators are biased. In order to estimate the parameters of the model consistently, the indirect estimation procedure suggested by Gourieroux et al. (1993) is applied. To demonstrate this method, first a simulation study is performed and then in a second step, two real data sets are used. In the latter case, continuous regressors are transformed into categorical variables to study the behavior of the estimation procedure. In general, the indirect estimators lead to adequate results

Time Series of Count Data : Modelling and Estimation

This paper compares various models for time series of counts which can account for discreetness, overdispersion and serial correlation. Besides observation- and parameter-driven models based upon corresponding conditional Poisson distributions, we also consider a dynamic ordered probit model as a flexible specification to capture the salient features of time series of counts. For all models, we present appropriate efficient estimation procedures. For parameter-driven specifications this requires Monte Carlo procedures like simulated Maximum likelihood or Markov Chain Monte-Carlo. The methods including corresponding diagnostic tests are illustrated with data on daily admissions for asthma to a single hospital. --Efficient Importance Sampling,GLARMA,Markov Chain Monte-Carlo,Observation-driven model,Parameter-driven model,Ordered Probit

Das Innovationsverhalten der baden-württembergischen Unternehmen : eine Auswertung der ZEW/infas-Innovationserhebung 1993, erarbeitet für den Innovationsbeirat Baden-Württemberg

Die Landesregierung Baden-Württemberg hat die Förderung unternehmerischer Innovationsaktivitäten zu einem Schwerpunkt ihrer Wirtschaftspolitik erhoben: Dies manifestiert sich - neben anderem - in der Einrichtung des baden-württembergischen Innovationsbeirates. Dieses unabhängige und interdisziplinär aus Wissenschaftlern verschiedener Fachrichtungen, Unternehmenspraktikern und spezialisierten Politikern zusammengesetzte Gremium hat sich zur Aufgabe gesetzt, technologische Zukunftsstrategien zu entwickeln und Richtlinien für eine innovationsfördernde Politik aufzuzeigen

Analyzing ordered categorical data derived from elliptically symmetric distributions

The polychoric correlation is an ML estimator for the correlation parameter between two latent variables. Each latent variable is only observed as an ordered categorical indicator. This estimator is based on an assumption on the joint distribution for the latent variables which in this case is the bivariate standard normal distribution. We perform a simulation study applying the polychoric correlation based on normality if the true distribution is in fact an elliptically symmetric distribution. The results show that the polychoric correlation is robust in the sense that the true correlation between the latent variables is estimated only with small bias if the true distribution is not too leptokurtic and also not too platykurtic. These results imply that in practical applications the polychoric correlation can be applied obtaining meaningful results even if tests suggest that the assumed normal distribution is not appropriate. Basically the same results are obtained if one latent variable is observed directly and the ML-estimator based on normality (polyserial correlation) is applied

Rivalry and innovation races

Based on an extended game-theoretic innovation-race model, we derive some Schumpeterian hypotheses of the impact of technological rivalry, market power, technological opportunities and market size on the timing of product and process innovations. Using innovation data at the firm level in the German industrial sector, we estimate various versions of an econometric specification of the model with dichotomous innovation data by using a univariate binary probit model with qualitative regressor variables. Our empirical results are consistent with the derived hypotheses that intense rivalry, favorable technological opportunities and high demand expectations spur innovative activity, while the effect of market power is ambiguous

Financing constraints and the timing of innovations in the German services sector

Using newly available data at the firm level, this study provides convincing evidence of the importance of financial constraints in explaining the timing of innovations in the German services sector. Based on a dynamic model of firms' optimal R&D behavior under financial constraints, we estimate various versions of an econometric specification of the model with dichotomous innovation data by using a univariate ordered probit model. Our results are consistent with the theoretical view that, because of capital markets imperfections, internal finance should be an important determinant of innovative activities by private firms in the manufacturing sector as well as in the services sector

Total area of spontaneous portosystemic shunts independently predicts hepatic encephalopathy and mortality in liver cirrhosis

Background & Aims: Spontaneous portosystemic shunts (SPSS) frequently develop in liver cirrhosis. Recent data suggested that the presence of a single large SPSS is associated with complications, especially overt hepatic encephalopathy (oHE). However, the presence of >1 SPSS is common. This study evaluates the impact of total cross-sectional SPSS area (TSA) on outcomes in patients with liver cirrhosis. Methods: In this retrospective international multicentric study, CT scans of 908 cirrhotic patients with SPSS were evaluated for TSA. Clinical and laboratory data were recorded. Each detected SPSS radius was measured and TSA calculated. One-year survival was the primary endpoint and acute decompensation (oHE, variceal bleeding, ascites) was the secondary endpoint. Results: A total of 301 patients (169 male) were included in the training cohort. Thirty percent of all patients presented with >1 SPSS. A TSA cut-off of 83 mm2 was used to classify patients with small or large TSA (S-/L-TSA). Patients with L-TSA presented with higher model for end-stage liver disease score (11 vs. 14) and more commonly had a history of oHE (12% vs. 21%, p <0.05). During follow-up, patients with L-TSA experienced more oHE episodes (33% vs. 47%, p <0.05) and had lower 1-year survival than those with S-TSA (84% vs. 69%, p <0.001). Multivariate analysis identified L-TSA (hazard ratio 1.66; 95% CI 1.02–2.70, p <0.05) as an independent predictor of mortality. An independent multicentric validation cohort of 607 patients confirmed that patients with L-TSA had lower 1-year survival (77% vs. 64%, p <0.001) and more oHE development (35% vs. 49%, p <0.001) than those with S-TSA. Conclusion: This study suggests that TSA >83 mm2 increases the risk for oHE and mortality in patients with cirrhosis. Our results support the clinical use of TSA/SPSS for risk stratification and decision-making in the management of patients with cirrhosis. Lay summary: The prevalence of spontaneous portosystemic shunts (SPSS) is higher in patients with more advanced chronic liver disease. The presence of more than 1 SPSS is common in advanced chronic liver disease and is associated with the development of hepatic encephalopathy. This study shows that total cross-sectional SPSS area (rather than diameter of the single largest SPSS) predicts survival in patients with advanced chronic liver disease. Our results support the clinical use of total cross-sectional SPSS area for risk stratification and decision-making in the management of SPSS.Jonel Trebicka is supported by grants from the Deutsche Forschungsgemeinschaft (SFB TRR57, CRC1382), Cellex Foundation and European Union’s Horizon 2020 research and innovation program GALAXY study (No. 668031), LIVERHOPE (No. 731875) and MICROB-PREDICT (No. 825694) and the Cellex Foundation. Joan Genescà is a recipient of a Research Intensification grant from Instituto de Salud Carlos III, Spain. The study was partially funded by grants PI15/00066, and PI18/00947 from Instituto de Salud Carlos III and co-funded by European Union (ERDF/ESF, “Investing in your future”). Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivasis supported by Instituto de Salud Carlos III. Macarena Simón-Talero is a recipient of the grant JR 17/00029 from Instituto de Salud Carlos II

Testing the Ricardian trade theory

SIGLEAvailable from Bibliothek des Instituts fuer Weltwirtschaft, ZBW, Duesternbrook Weg 120, D-24105 Kiel / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekDEGerman

Indirect Estimation of Linear Models with Ordinal Regressors. A Monte Carlo Study and some Empirical Illustrations.

This paper investigates the effects of ordinal regressors in linear regression models. Each ordered categorical variable is interpreted as a rough measurement of an underlying continuous variable as it is often done in microeconometrics for the dependent variable. It is shown that using ordinal indicators only leads to correct answers in a few special cases. In most situations, the usual estimators are biased. In order to estimate the parameters of the model consistently, the indirect estimation procedure suggested by Gourieroux et al. (1993) is applied. To demonstrate this method, first a simulation study is performed and then in a second step, two real data sets are used. In the latter case, continuous regressors are transformed into categorical variables to study the behavior of the estimation procedure. In general, the indirect estimators lead to adequate results